Course content

In this course you will get acquainted with the fundamental theories and application of multilevel models. The focus will be on using these methods for applied research. You will also gain practical competency in statistical software for analyzing data.

The course covers the following key topics

  1. Multilevel data structures, variance components, and ecological fallacy
  2. Random intercepts and random slopes
  3. Contextual and cross-level interaction models
  4. Latent covariate and multilevel path models

Learning outcome

Knowledge

  • recognize the general principles of multilevel models
  • understand the key assumptions that underlie these models and methods
  • understand the principles of model selection and associated inferences

Skills

  • select, apply, and interpret the results of a multilevel model that is appropriate for the data and the research question at hand
  • test key assumptions and offer possible solutions to violations
  • write up the results of an analysis in an appropriate way
  • analyze data with help of existing statistical software packages

Competencies

  • demonstrate a facility with multilevel modeling to answer well-defined research questions
  • interpret published scientific research that uses these models and methods
  • evaluate the tenability of associated inferences and knowledge claims

Admission to the course

Students who are admitted to study programmes at UiO must each semester register which courses and exams they wish to sign up for in Studentweb.

If you are not already enrolled as a student at UiO, please see our information about admission requirements and procedures.

PhD candidates can take the PhD version of the course: UV9253

Formal prerequisite knowledge

MAE4000 Data Science or equivalent.

Overlapping courses

Teaching

This course combines lectures and computer labs with data analysis tasks in statistical software environments.

Obligatory course components:

  • 80% attendance requirement for the lectures
  • computer lab participation and completion of computer lab exercises

Examination

The exam consists of a 4 hour individual written examination covering all course material and topics.

You need to have successfully completed the obligatory course components before being allowed to sit the exam. If you do not fulfill these requirements, you must submit a written request to apply for an additional assignment prior to sitting the exam. The application must document stated reasons for absence beyond your control.

Previous exams

Examination support material

No examination support material is allowed.

Language of examination

The examination text is given in English, and you submit your response in English.

Grading scale

Grades are awarded on a scale from A to F, where A is the best grade and F is a fail. Read more about the grading system.

Resit an examination

More about examinations at UiO

You will find further guides and resources at the web page on examinations at UiO.

Last updated from FS (Common Student System) May 3, 2024 11:14:08 AM

Facts about this course

Level
Master
Credits
5
Teaching
Autumn

Course offered for the first time in autumn 2019, then every autumn after that

Exams offered for the first time in autumn 2019, then every autumn after that

Examination
Autumn
Teaching language
English